PL-300 Practice Test 34 — 15 Questions

Question 1

Which TWO of the following are best practices when designing star schemas in Power BI? (Select two.)

Accepted Answer

Store numeric measures in fact tables.. Option A is correct because fact tables should contain numeric, additive measures (such as Sales Amount or Quantity) that can be aggregated by the Power BI engine, which is the core purpose of a star schema fact table. Option C is correct because descriptive attributes (such as Product Name, Category, or Customer City) belong in dimension tables, where they serve as the "by" fields for slicing and filtering the numeric measures in the fact table. Option B is not a best practice because row-level security should be implemented with DAX filter expressions on dimension tables (or via roles), not by adding calculated columns to fact tables, which bloats the model and hurts performance. Option D is wrong because fact tables should stay narrow and contain only keys and measures; adding many columns for filtering increases model size and degrades compression and query performance. Option E is incorrect because star schemas deliberately use denormalized, flattened dimension tables to reduce the number of joins and improve query performance in Power BI.

Answer

Use calculated columns in fact tables for row-level security.

Answer

Include many columns in fact tables for filtering.

Answer

Normalize dimension tables to reduce redundancy.

Question 2

Which THREE data sources can be used with Power BI Dataflows? (Choose three.)

Accepted Answer

OData feed. Power BI Dataflows are built on the Power Query Online engine, so any connector available in Power Query Online can serve as a data source. Option C (OData feed) is correct because OData is a standard REST-based protocol connector supported in Power Query Online, allowing dataflows to ingest from OData v3/v4 endpoints. Option D (Azure SQL Database) is correct because Azure SQL Database is a supported cloud database connector in Power Query Online, enabling direct query or import into the dataflow's CDM storage. Option E (SharePoint Online list) is correct because SharePoint Online lists are a native cloud connector in Power Query Online, letting dataflows pull list data via the SharePoint REST API. Option A (Power BI dataset) is not a valid dataflow source because dataflows feed into datasets, not the reverse, and Power Query Online does not expose a Power BI dataset connector. Option B (Excel file stored on local drive) is not valid because Power Query Online runs in the cloud and cannot access a local drive path; a personal gateway or uploading to OneDrive/SharePoint would be required.

Answer

Power BI dataset

Answer

Excel file stored on local drive

Question 3

Which TWO actions are required when configuring a Power BI dataset to use incremental refresh?

Accepted Answer

Set the incremental refresh policy in the dataset settings.. Option E is correct because incremental refresh in Power BI requires two Power Query parameters named exactly rangeStart and rangeEnd (both of type DateTime), which define the filter window applied to the table's date column so Power BI can partition and refresh only the relevant ranges. Option D is correct because, after publishing the dataset, you must configure the incremental refresh policy (via the dataset's settings in the Power BI service, or by right-clicking the table in Power BI Desktop and selecting Incremental refresh) to specify the historical and incremental periods that determine how partitions are created and refreshed. Option A is incorrect because incremental refresh works with Import mode datasets and does not require DirectQuery storage mode. Option B is incorrect because query caching is a separate performance feature and is not a prerequisite for incremental refresh. Option C is incorrect because Power BI automatically manages the refresh history and partition metadata internally; no user-created calculated table is needed.

Answer

Set the dataset storage mode to DirectQuery.

Answer

Enable query caching on the dataset.

Answer

Create a calculated table to store the refresh history.

Question 4

Which THREE of the following are valid considerations when using Power BI DirectQuery mode?

Accepted Answer

Queries are sent to the underlying data source in real time.. Option C is correct because DirectQuery does not cache or import data into Power BI; instead, every visual interaction generates a query that is passed through to the underlying source (e.g., SQL Server, Azure Synapse, Oracle) in real time, so results reflect the source's current state. Option D is correct because row-level security can be defined in the Power BI model and, for DirectQuery sources, the RLS filters are translated into the native query sent to the data source, restricting the rows each user can see. Option E is correct because DirectQuery must translate DAX into the source's query language, so certain DAX functions and constructs (for example, some time intelligence and parent-child functions) are unsupported or behave differently, and Power BI will flag them as not supported in DirectQuery mode. Option A is wrong because importing data describes Import mode, not DirectQuery, which leaves the data in the source. Option B is wrong because relationships between tables can still be created in a DirectQuery model; they are simply used to generate the appropriate joins in the queries sent to the source.

Answer

Data is imported into the Power BI dataset.

Answer

You cannot create relationships between tables.

Question 5

You are reviewing a Power Query that imports data from SQL Server. The exhibit shows the M code. The SQL query filters records after a date, then Power Query filters rows with OrderQty > 10, and then groups by ProductID. What is a potential performance issue with this approach?

Accepted Answer

The filter on OrderQty > 10 should be included in the SQL query to reduce the amount of data transferred.. Pushing the `OrderQty > 10` filter into the SQL query reduces the amount of data transferred from SQL Server to Power Query. In Power Query, data is loaded into memory before transformations; filtering earlier in the source query minimizes memory usage and network latency, which is a key performance optimization in Power BI data loading.

Answer

The query will fail because the SQL query uses '>' with a string.

Answer

The SQL query should use a parameter for the date instead of a hardcoded value.

Answer

The grouping should be done in SQL to reduce data volume.

Question 6

You are using Power Query to combine data from multiple CSV files in a folder. Each file has the same structure. You want to append all rows into a single table. Which Power Query function should you use?

Accepted Answer

Combine Files from the folder connector.. The 'Combine Files' transformation in Power Query is specifically designed to import and append multiple CSV files from a folder into a single table. When you connect to a folder using the 'From Folder' connector, Power Query automatically generates a 'Combine Files' step that uses the 'Table.Combine' function under the hood, which appends all rows from identically structured files into one unified table.

Answer

Group By.

Answer

Append Queries.

Answer

Merge Queries as new.

Question 7

You have a measure as shown in the exhibit. The sales amount is not accumulating correctly; instead, it shows the total sales for all dates, regardless of the selected date filter. What is the problem?

Accepted Answer

The ALL('Date') function removes the filter context, so the calculation returns total sales for all dates.. Using ALL('Date') within CALCULATE removes the filter context on the Date table, causing the measure to return the total sales across all dates, not the current date context. Option A is incorrect; ALLEXCEPT would keep certain filters, but the problem here is specifically the removal of all date filters by ALL. Option C is incorrect; using MIN versus MAX in VAR SelectedDate does not cause the described behavior; the issue is the ALL function. Option D is incorrect; an inactive relationship would prevent proper filtering but would not result in the measure returning the total for all dates; the symptom would be different.

Answer

The measure should use ALLEXCEPT instead of ALL.

Answer

The VAR SelectedDate should be MIN instead of MAX.

Answer

The relationship between Sales and Date is inactive.

Question 8

You connect to a large Azure SQL Database table with over 100 million rows. You need to create a report that shows sales by month for the current year only. Which data reduction technique should you use in Power Query to minimize data load?

Accepted Answer

In Power Query, apply a date filter on the source query so only current year data is imported.. Applying a date filter in Power Query at the source query level ensures that only rows from the current year are imported into the Power BI data model. This reduces the data volume from over 100 million rows to a fraction, minimizing memory usage and improving refresh performance. Power Query pushes the filter down to the Azure SQL Database using a WHERE clause in the SQL query, so only the filtered data is transferred over the network.

Answer

Import all data and then remove columns that are not needed.

Answer

Load all data and filter using a visual-level filter in the report.

Answer

Use a calculated table in DAX to filter the data.

Question 9

You are a Power BI administrator. You need to audit all activities related to sharing reports and dashboards in the Power BI service. Which tool should you use?

Accepted Answer

Power BI activity log (via admin API or portal). The Power BI activity log provides a comprehensive record of all user activities within the Power BI service, including sharing reports and dashboards. Option A (Microsoft Purview compliance portal audit log) can capture some Power BI activities but is less specific and may not include all sharing events. Option B (Azure diagnostic settings) exports telemetry data to other destinations and is not designed for direct auditing of user actions. Option D (Microsoft Sentinel) is a SIEM tool that can ingest logs but is not the primary tool for auditing Power BI activities. The Power BI activity log is the correct choice as it is purpose-built for auditing Power BI user activities.

Answer

Microsoft Purview compliance portal audit log

Answer

Azure diagnostic settings for Power BI

Answer

Microsoft Sentinel

Question 10

You are connecting to a large CSV file (10 GB) stored in Azure Blob Storage. You need to load the data into Power BI with optimal performance. Which THREE practices should you follow? (Choose three.)

Accepted Answer

Use Parquet format instead of CSV if possible.. Option A is correct because Parquet is a columnar, compressed format that Power BI can read far more efficiently than CSV, reducing file size and scan time for a 10 GB dataset. Option C is correct because splitting the large CSV into multiple smaller files in the same folder enables Power BI's parallel loading and folder-combine pattern, improving throughput versus reading one monolithic file. Option D is correct because applying row filters in Power Query early reduces the volume of data pulled into the model, lowering memory and refresh cost. Option B is wrong because importing all columns then hiding them still loads every column into the model, wasting memory and bandwidth. Option E is wrong because the on-premises data gateway is only needed for on-premises data sources, not for a native cloud source like Azure Blob Storage.

Answer

Import all columns and use Power BI to hide unused ones.

Answer

Use the on-premises data gateway to connect to Azure Blob Storage.

Question 11

You need to combine data from three different SharePoint lists into a single table for analysis. The lists have different column names but contain similar data. What is the best approach in Power Query?

Accepted Answer

Use 'Append Queries' and then rename columns to match.. Append Queries is the correct approach because it stacks rows from multiple tables (SharePoint lists) into a single table, which is exactly what you need when combining data with similar structures but different column names. After appending, you can rename columns to unify the schema. This is the standard Power Query method for row-level concatenation of tables.

Answer

Use 'Unpivot Columns' to transform the data.

Answer

Use 'Group By' to combine values.

Answer

Use 'Merge Queries' on a common key column.

Question 12

You have a dataset with a column 'FullName' containing values like 'John Doe'. You need to split this column into 'FirstName' and 'LastName' using the space delimiter. Which Power Query transformation should you use?

Accepted Answer

Split Column by Delimiter.. The 'Split Column by Delimiter' transformation in Power Query is specifically designed to divide a single text column into multiple columns based on a specified delimiter, such as a space. In this scenario, selecting the column 'FullName' and using 'Split Column > By Delimiter' with a space delimiter will correctly separate 'John Doe' into 'FirstName' (John) and 'LastName' (Doe). This is the standard approach for parsing delimited text within Power Query.

Answer

Merge Columns.

Answer

Extract Text.

Answer

Replace Values.

Question 13

You are designing a Power BI data model for a sales analysis. The source data has a table 'Orders' with columns: OrderID, CustomerID, ProductID, OrderDate, Quantity, UnitPrice. You also have a table 'Customers' with CustomerID, CustomerName, and 'Products' with ProductID, ProductName. You need to create a star schema. What should you do?

Accepted Answer

Keep Customers and Products as separate dimension tables, and Orders as the fact table. In a star schema, a single fact table (Orders) stores quantitative measures (Quantity, UnitPrice) and foreign keys (CustomerID, ProductID) that link to dimension tables (Customers, Products) containing descriptive attributes. This design optimizes query performance by reducing joins and enabling efficient aggregation, which is a best practice for Power BI data modeling.

Answer

Split Orders into multiple fact tables by year

Answer

Create a snowflake schema by normalizing Customers and Products further

Answer

Merge Customers and Products into a single dimension table

Question 14

You need to allow users to ask questions about their data using natural language. Which Power BI feature should you enable?

Accepted Answer

Q&A visual. The Q&A visual in Power BI allows users to ask questions about their data using natural language, automatically generating visualizations based on the query. This feature is specifically designed for natural language querying, making it the correct choice for enabling users to interact with data conversationally.

Answer

Key Influencers visual

Answer

Quick Insights

Answer

Copilot

Question 15

You are reviewing a Power Query M expression in the advanced editor. The exhibit shows the query. What is the final output of this query?

Accepted Answer

A table with total sales amount per customer for orders after 2023. The query filters the Sales table to keep only rows where the OrderDate is in 2024 or later (i.e., after 2023), then groups by CustomerID, summing the SalesAmount for each customer. The final output is a table with one row per customer showing their total sales amount for orders placed after 2023.

Answer

A table with total sales amount per customer for all orders

Answer

A table with all sales records after 2023

Answer

A table with all sales records after 2023, excluding Discount column